Manager, GPU Accelerated Data Analytics

Nvidia

Confirmed live yesterday High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Santa Clara, CANew York, NY
Salary: $224,000–$356,500 / yr
Posted: 37 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $215k

This role $290k

$150k most similar roles pay here $379k

This role pays more than 91% of similar roles. Most pay $180,500–$248,687 — the shaded band above. At the midpoint, this role pays about $290k versus about $215k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Manager, GPU Accelerated Data Analytics

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Manager, GPU Accelerated Data Analytics joins the Developer Technology Engineering team to lead a distributed group of performance engineers. This role focuses on researching and developing innovative techniques to optimize complex workloads across cloud and on-premise environments, specifically targeting mission-critical tasks like database operations, data preprocessing, compression, video transcoding, and web servers. The manager will drive technical excellence by making software design decisions, influencing architecture roadmaps, and collaborating with cross-functional partners to advocate for next-generation hardware and software products. Candidates must possess expertise in CPU and GPU architecture fundamentals, low-level performance optimization, and GPU parallel programming using CUDA. Proficiency in C/C++ and strong algorithmic skills are required. The role addresses the challenge of modernizing data centers by replacing traditional CPU-heavy workloads with accelerated computing solutions to reduce costs and power consumption for large-scale enterprise applications.

Skills

CUDA C++ C GPU Architecture Parallel Computing SQL Vector Databases Storage Technologies Deep Learning

What you'll do

Research and develop innovative techniques to optimize performance for complex workloads in cloud and on-premise environments.
Lead software design decisions and influence the hardware architecture roadmap based on performance needs.
Manage and mentor a distributed team of performance engineers to grow their technical expertise.
Develop implementations that reduce cost and power consumption using NVIDIA's CPU and GPU platforms.
Communicate technical solutions and strategic initiatives to multi-functional teams and company leadership.
Advocate for next-generation hardware and software products that address the needs of the developer community.
Execute high-impact projects to improve the adoption of NVIDIA’s performance-focused technologies.

What we're looking for

MS or PhD in Computer Science, Computer Engineering, or a related computationally focused science degree.
Relevant experience with in a technical role.
At least 3 years of experience in an engineering leadership role.
Hands-on experience in low-level performance optimization and GPU parallel programming, such as CUDA.
Programming fluency in C/C++ with a deep understanding of algorithms and software development.
In-depth expertise with CPU and GPU architecture fundamentals.
Proven track record of building high-performing teams by attracting and hiring top engineering talent.
Strong communication skills to lead cross-functional collaboration and present technical solutions.

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